A Smartphone-Integrated Molecularly Imprinted Fluorescence Sensor for Visual Detection of Chlortetracycline Based on N,P-Codoped Carbon Dots Decorated Iron-Based Metal-Organic Frameworks.

The residue of chlortetracycline is potentially hazardous to human health; it is meaningful to exploit a portable, rapid, sensitive, and selective method for detection of chlortetracycline (CTC). In this study, a novel fluorescence bionic sensing probe (NH2-MIL-53&N,P-CDs@MIP) was successfully prepared based on the nitrogen and phosphorus codoped carbon dots decorated iron-based metal-organic frameworks combining with molecular imprinted polymer for the detection of CTC. A fluorescence intensity-responsive "on-off" detection of CTC on account of the inner-filter effect (IFE) was achieved by NH2-MIL-53&N,P-CDs@MIP. Under the optimal conditions, the fluorescence quenching degree of NH2-MIL-53&N,P-CDs@MIP presented a good linear relationship with the CTC concentration in the range 0.06-30 µg mL-1 and the limit of detection (LOD) was 0.019 µg mL-1. The fluorescent probe was applied to detect CTC in milk samples, and experimental results showed a good recovery rate (88.73%-96.28%). Additionally, a smartphone-integrated fluorescence sensing device based on NH2-MIL-53&N,P-CDs@MIP was exploited to replace the expensive and bulky fluorescence spectrophotometer for quantitative determination of CTC with the LOD of 0.033 µg mL-1. The sensing system showed high selectivity, strong stability, high specificity, and portability, which provide a great strategy for the quantitative detection of antibiotic residue.

The participation of clinical pharmacists in the treatment of patients with central nervous system infection can improve the effectiveness and appropriateness of anti-infective treatments: a retrospective cohort study.

Background: Central nervous system infection (CNSI) treatment in hospital neurosurgery emphasizes the importance of optimizing antimicrobial therapy. Timely and appropriate empiric antibiotic treatment is critical for managing patients with bacterial meningitis. Objectives: To evaluate the activities of clinical pharmacists in the anti-infective treatment of patients with CNSI in neurosurgery. Method: A single-center retrospective cohort study was carried out from January 2021 to March 2023 at a tertiary teaching hospital in China. The study sample included a group that received pharmacy services and a group that did not. In the pharmacy services group, the anti-infective treatment plan was led and developed by pharmacists. Pharmaceutical care, including medication therapy and all CNSI treatment regimens, was administered in daily unit rounds by pharmacists. Baseline demographics, treatment outcomes, and rational use of antibiotics were compared between the two groups, and the impact of a antimicrobial stewardship (AMS) program was evaluated. Results: Of the 306 patients assessed according to the inclusion and exclusion criteria, 151 patients were included, and 155 patients were excluded due to abnormal data and missing information on antibiotic costs or antimicrobial use. Eventually, 73 were included in the pharmacy services group and 78 in the group without pharmacist participation. The antibiotic use density (AUD) of the pharmacy services group decreased from 167.68 to 127.63 compared to the group without pharmacist participation. After the pharmacist services, the AUD for linezolid decreased from 9.15% to 5.23% and that for miscellaneous agents decreased from 17.91% to 6.72%. The pharmacy services group had better improvement (p < 0.05) and a significantly higher score for the rational use of antibiotics (p < 0.05) than the group without pharmacist participation. Conclusion: The clinical pharmacist services evaluation results demonstrated an essential role of clinical pharmacist-led AMS programs in the effective and appropriate use of anti-infective treatments in neurosurgery with patients with CNSI.

Development of Magnetic Lateral Flow and Direct Competitive Immunoassays for Sensitive and Specific Detection of Halosulfuron-Methyl Using a Novel Hapten and Monoclonal Antibody.

Halosulfuron-methyl (HM) is widely used for the removal of noxious weeds in corn, sugarcane, wheat, rice, and tomato fields. Despite its high efficiency and low toxicity, drift to nontarget crops and leaching of its metabolites to groundwater pose potential risks. Considering the instability of HM, the pyrazole sulfonamide of HM was used to generate a hapten and antigen to raise a high-quality monoclonal antibody (Mab, designated 1A91H11) against HM. A direct competitive immunoassay (dcELISA) using Mab 1A91H11 achieved a half-maximal inhibitory concentration (IC50) of 1.5 × 10-3 mg/kg and a linear range of 0.7 × 10-3 mg/kg-10.7 × 10-3 mg/kg, which was 10 times more sensitive than a comparable indirect competitive ELISA (icELISA) and more simple to operate. A spiking recovery experiment performed in tomato and maize matrices with 0.01, 0.05, and 0.1 mg/kg HM had average recoveries within 78.9-87.9% and 103.0-107.4% and coefficients of variation from 1.1-6.8% and 2.7-6.4% in tomato and maize, respectively. In addition, a magnetic lateral flow immunoassay (MLFIA) was developed for quantitative detection of low concentrations of HM in paddy water. Compared with dcELISA, the MLFIA exhibited 3.3- to 50-fold higher sensitivity (IC50 0.21 × 10-3 mg/kg). The average recovery and RSD of the developed MLFIA ranged from 81.5 to 92.5% and 5.4 to 9.7%. The results of this study demonstrated that the developed dcELISA and MLFIA are suitable for rapid detection of HM residues in tomato and maize matrices and paddy water, respectively, with acceptable accuracy and precision.

Modeling and insights into the structural characteristics of endocrine-disrupting chemicals.

Endocrine-disrupting chemicals (EDCs) can cause serious harm to human health and the environment; therefore, it is important to rapidly and correctly identify EDCs. Different computational models have been proposed for the prediction of EDCs over the past few decades, but the reported models are not always easily available, and few studies have investigated the structural characteristics of EDCs. In the present study, we have developed a series of artificial intelligence models targeting EDC receptors: the androgen receptor (AR); estrogen receptor (ER); and pregnane X receptor (PXR). The consensus models achieved good predictive results for validation sets with balanced accuracy values of 87.37%, 90.13%, and 79.21% for AR, ER, and PXR binding assays, respectively. Analysis of the physical-chemical properties suggested that several chemical properties were significantly (p < 0.05) different between EDCs and non-EDCs. We also identified structural alerts that can indicate an EDC, which were integrated into the web server SApredictor. These models and structural characteristics can provide useful tools and information in the discrimination and mechanistic understanding of EDCs in drug discovery and environmental risk assessment.

Safety of butylphthalide and edaravone in patients with ischemic stroke: a multicenter real-world study.

BACKGROUND: Butylphthalide (NBP) and edaravone (EDV) injection are common acute ischemic stroke medications in China, but there is a lack of large real-world safety studies on them. This study aimed to determine the incidence of adverse events, detect relevant safety signals, and assess the risk factors associated with these medications in real-world populations. METHODS: In this study, data of acute ischemic stroke patients were extracted from the electronic medical record database of six tertiary hospitals between January 2019 and August 2021. Baseline confounders were eliminated using propensity score matching. The drugs' safety was estimated by comparing the results of 24 laboratory tests standards on liver function, kidney function, lipid level, and coagulation function. The drugs' relative risk was estimated by logistic regression. A third group with patients who did not receive NBP or EDV was constructed as a reference. Prescription sequence symmetry analysis was used to evaluate the associations between adverse events and NBP and EDV, respectively. RESULTS: 81,292 patients were included in this study. After propensity score matching, the NBP, EDV, and third groups with 727 patients in each group. Among the 15 test items, the incidence of adverse events was lower in the NBP group than in the EDV group, and the differences were statistically significant. The multivariate logistic regression equation revealed that NBP injection was not a promoting factor for abnormal laboratory test results, whereas EDV had statistically significant effects on aspartate transaminase, low-density lipoprotein cholesterol and total cholesterol. Prescription sequence symmetry analysis showed that NBP had a weak correlation with abnormal platelet count. EDV had a positive signal associated with abnormal results in gamma-glutamyl transferase, alanine aminotransferase, aspartate aminotransferase, prothrombin time, and platelet count. CONCLUSIONS: In a large real-world population, NBP has a lower incidence of adverse events and a better safety profile than EDV or other usual medications.

Competitive fluorescent immunosensor based on catalytic hairpin self-assembly for multiresidue detection of organophosphate pesticides in agricultural products.

Simple and rapid multiresidue trace detection of organophosphate pesticides (OPs) is extremely important for various reasons, including food safety, environmental monitoring, and national health. Here, a catalytic hairpin self-assembly (CHA)-based competitive fluorescent immunosensor was developed to detect OPs in agricultural products, involving enabled dual signal amplification followed by a CHA reaction. The developed method could detect 0.01-50 ng/mL triazophos, parathion, and chlorpyrifos, with limits of detection (LODs) of 0.012, 0.0057, and 0.0074 ng/mL, respectively. The spiked recoveries of samples measured using this assay ranged from 82.8 % to 110.6 %, with CV values ranging between 5.5 % and 18.5 %. This finding suggests that the CHA-based competitive fluorescent immunosensor is a reliable and accurate method for detecting OPs in agricultural products. The results correlated well with those obtained from the liquid chromatography-tandem mass spectrometry (LC-MS/MS) method, indicating that the CHA-based biosensor is able to accurately detect OPs and can be used as a reliable alternative to the LC-MS/MS method. Additionally, the CHA-based biosensor is simpler and faster than LC-MS/MS, which makes it a more practical and cost-effective option for the detection of OPs. In summary, the CHA-based competitive fluorescent immunosensor can be considered a promising approach for trace analysis and multiresidue determination of pesticides, which can open up new horizons in the fields of food safety, environmental monitoring, and national health.

SARS-CoV-2 vaccines are not associated with hypercoagulability in apparently healthy people.

Background: SARS-CoV-2 adenoviral vector DNA vaccines have been linked to the rare but serious thrombotic postvaccine complication vaccine-induced immune thrombotic thrombocytopenia. This has raised concerns regarding the possibility of increased thrombotic risk after any SARS-CoV-2 vaccines. Objectives: To investigate whether SARS-CoV-2 vaccines cause coagulation activation leading to a hypercoagulable state. Methods: This observational study included 567 health care personnel; 521 were recruited after the first dose of adenoviral vector ChAdOx1-S (Vaxzevria, AstraZeneca) vaccine and 46 were recruited prospectively before vaccination with a messenger RNA (mRNA) vaccine, either Spikevax (Moderna, n = 38) or Comirnaty (Pfizer-BioNTech, n = 8). In the mRNA group, samples were acquired before and 1 to 2 weeks after vaccination. In addition to the prevaccination samples, 56 unvaccinated blood donors were recruited as controls (total n = 102). Thrombin generation, D-dimer levels, and free tissue factor pathway inhibitor (TFPI) levels were analyzed. Results: No participant experienced thrombosis, vaccine-induced immune thrombotic thrombocytopenia, or thrombocytopenia (platelet count <100 × 109/L) 1 week to 1 month postvaccination. There was no increase in thrombin generation, D-dimer level, or TFPI level in the ChAdOx1-S vaccine group compared with controls or after the mRNA vaccines compared with baseline values. Eleven of 513 (2.1%) participants vaccinated with ChAdOx1-S had anti-PF4/polyanion antibodies without a concomitant increase in thrombin generation. Conclusion: In this study, SARS-CoV-2 vaccines were not associated with thrombosis, thrombocytopenia, increased thrombin generation, D-dimer levels, or TFPI levels compared with baseline or unvaccinated controls. These findings argue against the subclinical activation of coagulation post-COVID-19 vaccination.

Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity.

Neurotoxicity can be resulted from many diverse clinical drugs, which has been a cause of concern to human populations across the world. The detection of drug-induced neurotoxicity (DINeurot) potential with biological experimental methods always required a lot of budget and time. In addition, few studies have addressed the structural characteristics of neurotoxic chemicals. In this study, we focused on the computational modeling for drug-induced neurotoxicity with machine learning methods and the insights into the structural characteristics of neurotoxic chemicals. Based on the clinical drug data with neurotoxicity effects, we developed 35 different classifiers by combining five different machine learning methods and seven fingerprint packages. The best-performing model achieved good results on both 5-fold cross-validation (balanced accuracy of 76.51%, AUC value of 0.83, and MCC value of 0.52) and external validation (balanced accuracy of 83.63%, AUC value of 0.87, and MCC value of 0.67). The model can be freely accessed on the web server DINeuroTpredictor (http://dineurot.sapredictor.cn/). We also analyzed the distribution of several key molecular properties between neurotoxic and non-neurotoxic structures. The results indicated that several physicochemical properties were significantly different between the neurotoxic and non-neurotoxic compounds, including molecular polar surface area (MPSA), AlogP, the number of hydrogen bond acceptors (nHAcc) and donors (nHDon), the number of rotatable bonds (nRotB), and the number of aromatic rings (nAR). In addition, 18 structural alerts responsible for chemical neurotoxicity were identified. The structural alerts have been integrated with our web server SApredictor (http://www.sapredictor.cn). The results of this study could provide useful information for the understanding of the structural characteristics and computational prediction for chemical neurotoxicity.

Modeling and insights into the structural characteristics of drug-induced autoimmune diseases.

The incidence and complexity of drug-induced autoimmune diseases (DIAD) have been on the rise in recent years, which may lead to serious or fatal consequences. Besides, many environmental and industrial chemicals can also cause DIAD. However, there are few effective approaches to estimate the DIAD potential of drugs and other chemicals currently, and the structural characteristics and mechanism of action of DIAD compounds have not been clarified. In this study, we developed the in silico models for chemical DIAD prediction and investigated the structural characteristics of DIAD chemicals based on the reliable drug data on human autoimmune diseases. We collected 148 medications which were reported can cause DIAD clinically and 450 medications that clearly do not cause DIAD. Several different machine learning algorithms and molecular fingerprints were combined to develop the in silico models. The best performed model provided the good overall accuracy on validation set with 76.26%. The model was made freely available on the website http://diad.sapredictor.cn/. To further investigate the differences in structural characteristics between DIAD chemicals and non-DIAD chemicals, several key physicochemical properties were analyzed. The results showed that AlogP, molecular polar surface area (MPSA), and the number of hydrogen bond donors (nHDon) were significantly different between the DIAD and non-DIAD structures. They may be related to the DIAD toxicity of chemicals. In addition, 14 structural alerts (SA) for DIAD toxicity were detected from predefined substructures. The SAs may be helpful to explain the mechanism of action of drug induced autoimmune disease, and can used to identify the chemicals with potential DIAD toxicity. The structural alerts have been integrated in a structural alert-based web server SApredictor (http://www.sapredictor.cn). We hope the results could provide useful information for the recognition of DIAD chemicals and the insights of structural characteristics for chemical DIAD toxicity.

Zinc dendrite suppression by a novel additive combination for rechargeable aqueous zinc batteries.

With the advantages of low cost, good safety, and easy assembly, aqueous zinc batteries (AZBs) are expected to be a promising energy storage device. However, AZBs are compromised by Zn dendrites and the hydrogen evolution reaction. Herein, we use polyethylene glycol-200 (PEG-200) and benzylidene acetone (BDA) as additives in the electrolyte of AZBs in order to inhibit Zn dendrite growth and side reactions, thus improving the cycle performance of the Zn electrode. PEG-200 can be not only used as a co-solvent for BDA but also as a surfactant to achieve a uniform interfacial electric field. As a brightening agent, BDA forms a diffusion layer on the plating substrate, which increases the electrochemical polarization and nucleation overpotential, increases the number of active nucleation sites, and finally refines the grain size of the zinc deposit. The surface of the symmetric battery electrode with electrolyte containing PEG-200 additive is smooth after cycling, and dendrite formation is successfully suppressed. The Zn-Zn symmetric cell with additive-containing electrolyte has a higher nucleation overpotential and a cyclic stability for as long as 890 h (only 48 h for the unmodified symmetric cell). This is due to the adsorption of the additive on the negative electrode, which homogenizes the deposition interface and reduces the contact of the negative electrode with water.

A highly sensitive bio-barcode immunoassay for multi-residue detection of organophosphate pesticides based on fluorescence anti-quenching.

Balancing the risks and benefits of organophosphate pesticides (OPs) on human and environmental health relies partly on their accurate measurement. A highly sensitive fluorescence anti-quenching multi-residue bio-barcode immunoassay was developed to detect OPs (triazophos, parathion, and chlorpyrifos) in apples, turnips, cabbages, and rice. Gold nanoparticles were functionalized with monoclonal antibodies against the tested OPs. DNA oligonucleotides were complementarily hybridized with an RNA fluorescent label for signal amplification. The detection signals were generated by DNA-RNA hybridization and ribonuclease H dissociation of the fluorophore. The resulting fluorescence signal enables multiplexed quantification of triazophos, parathion, and chlorpyrifos residues over the concentration range of 0.01-25, 0.01-50, and 0.1-50 ng/mL with limits of detection of 0.014, 0.011, and 0.126 ng/mL, respectively. The mean recovery ranged between 80.3% and 110.8% with relative standard deviations of 7.3%-17.6%, which correlate well with results obtained by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The proposed bio-barcode immunoassay is stable, reproducible and reliable, and is able to detect low residual levels of multi-residue OPs in agricultural products.

SApredictor: An Expert System for Screening Chemicals Against Structural Alerts.

The rapid and accurate evaluation of chemical toxicity is of great significance for estimation of chemical safety. In the past decades, a great number of excellent computational models have been developed for chemical toxicity prediction. But most machine learning models tend to be "black box", which bring about poor interpretability. In the present study, we focused on the identification and collection of structural alerts (SAs) responsible for a series of important toxicity endpoints. Then, we carried out effective storage of these structural alerts and developed a web-server named SApredictor (www.sapredictor.cn) for screening chemicals against structural alerts. People can quickly estimate the toxicity of chemicals with SApredictor, and the specific key substructures which cause the chemical toxicity will be intuitively displayed to provide valuable information for the structural optimization by medicinal chemists.

Modeling and insights into the structural basis of chemical acute aquatic toxicity.

It has become a top global regulatory priority to prevent and control pollution from the release of synthetic chemicals, which continues to affect the aquatic communities. In the past decades, computational tools were largely used to significantly reduce the budget and time cost of chemical acute aquatic toxicity assessment. But the structural basis of toxic compounds was rarely analyzed. In the present study, we collected 1438, 485 and 961 chemicals with acute toxicity data records for three representative aquatic species, including Tetrahymena pyriformis, Daphnia magna, and Fathead minnow, respectively. A series of artificial intelligence models were developed using OCHEM tools. For each aquatic toxicity endpoint, a consensus model was developed based on the top performed individual models. The consensus models provided good performance on external validation sets with total accuracy values 96.88 %, 90.63 %, and 84.90 % for Tetrahymena pyriformis toxicity (TPT), Daphnia magna toxicity (DMT), and Fathead minnow toxicity (FMT), respectively. The models can be freely accessed via https://ochem.eu/article/146910. Moreover, the analysis of physical-chemical properties suggested that several key molecular properties of aquatic toxic compounds were significantly different with those of non-toxic compounds. Thus, these descriptors may be associated to chemical acute aquatic toxicity, and may be useful for the understand of chemical aquatic toxicity. Besides, in this study, the structural alerts for aquatic toxicity were detected using f-score and frequency ratio analysis of predefined substructures. A total of 112, 58 and 33 structural alerts were identified responsible for TPT, DMT, and FMT, respectively. These structural alerts could provide useful information for the mechanisms of chemical aquatic toxicity and visual alerts for environmental assessment. All the structural alerts were integrated in the web-server SApredictor (www.sapredictor.cn).

Design and Characterization of a Novel Hapten and Preparation of Monoclonal Antibody for Detecting Atrazine.

This study provides the first design and synthetic protocol for preparing highly sensitive and specific atrazine (ATR) monoclonal antibodies (mAbs). In this work, a previously unreported hapten, 2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine, was designed and synthesized, which maximally exposed the characteristic amino group ATR to an animal immune system to induce the expected antibody. The molecular weight of the ATR hapten was 259.69 Da, and its purity was 97.8%. The properties of the anti-ATR mAb were systematically characterized. One 9F5 mAb, which can detect ATR, was obtained with an IC50 value (the concentration of analyte that produced 50% inhibition of ATR) of 1.678 µg/L for ATR. The molecular weight for the purified 9F5 mAb was approximately 52 kDa for the heavy chain and 15 kDa for the light chain. The anti-ATR mAb prepared in this study was the IgG1 type. The working range of the standard curve (IC20 (the concentration of analyte that produced 20% inhibition of ATR)-IC80 (the concentration of analyte that produced 80% inhibition of ATR)) was 0.384 to 11.565 µg/L. The prepared anti-ATR mAb had high specificity, sensitivity, and affinity with low cross-reactivity. The prepared anti-ATR mAb could provide the core raw material for establishing an ATR immunoassay.

Comparative Effectiveness and Safety of Milrinone and Levosimendan as Initial Inotrope Therapy in Patients With Acute Heart Failure With Renal Dysfunction.

ABSTRACT: Levosimendan and milrinone are 2 effective inotropic drugs used to maintain cardiac output in acute heart failure (AHF). Using data from patients with AHF with and without abnormal renal function, we performed this single-center, retrospective cohort study to compare the effectiveness and safety of milrinone and levosimendan for the initial management of AHF. Patients admitted for heart failure between December 2016 and September 2019 who received levosimendan or milrinone as initial inotrope therapy in the cardiology department were identified. A total of 436 levosimendan and 417 milrinone patients with creatinine clearance (CrCl) ≥30 mL/min and 50 levosimendan and 71 milrinone patients with CrCl <30 mL/min or on dialysis were included. The primary outcome was a composite of changes in clinical status at 15 and 30 days after initial inotrope therapy discontinuation. Between subgroups of patients with CrCl ≥30 mL/min, there were no significant differences in primary outcomes; milrinone was associated with more frequent hypotension and cardiac arrhythmias during the infusion period (P < 0.01), while levosimendan was associated with more frequent cardiac arrhythmias within 48 hours after discontinuation (P < 0.05). Of the patients with CrCl <30 mL/min or on dialysis, more initial levosimendan than milrinone patients and those who switched to alternative inotropes experienced clinical worsening at 15 days and 30 days (P < 0.05). According to our results, patients with AHF with severe renal dysfunction should avoid initial inotrope therapy with levosimendan.

A competitive immunoassay for detecting triazophos based on fluorescent catalytic hairpin self-assembly.

A rapid detection method is introduced for residual trace levels of triazophos in water and agricultural products using an immunoassay based on catalytic hairpin self-assembly (CHA). The gold nanoparticle (AuNPs) surface was modified with triazophos antibody and sulfhydryl bio-barcode, and an immune competition reaction system was established between triazophos and its ovalbumin-hapten (OVA-hapten). The bio-barcode served as a catalyst to continuously induce the CHA reaction to achieve the dual signal amplification. The method does not rely on the participation of enzymes, and the addition of fluorescent materials in the last step avoids interfering factors, such as a fluorescence burst. The emitted fluorescence was detected at 489/521 nm excitation/emission wavelengths. The detection range of the developed method was 0.01-50 ng/mL for triazophos, and the limit of detection (LOD) was 0.0048 ng/mL. The developed method correlates well with the results obtained by LC-MS/MS, with satisfactory recovery and sensitivity. In sum, the designed method is reliable and provides a new approach to detect pesticide residues rapidly and quantitatively.

Obtaining a Monoclonal Antibody against a Novel Prometryn-Like Hapten and Characterization of Its Selectivity for Triazine Herbicides.

In this study, a previously unreported 3-((4-(isopropylamino)-6-(methylthio)-1,3,5-triazin-2-yl) amino) butyric acid hapten was designed and synthesized. This maximized the exposure of the antigen-determinant isopropyl of prometryn to the immune system in animals to induce the production of anticipated highly specific anti-prometryn antibodies. The hapten has a molecular weight of 285.37 Da. The compound was confirmed by nuclear magnetic resonance hydrogen spectroscopy (1H NMR), nuclear magnetic resonance carbon spectroscopy (13C NMR), and high-resolution mass spectrometry (HRMS). By using the active ester approach, immunogens and coated antigens were created. Bovine serum albumin (BSA) was used as an immunogen, along with the successfully produced hapten, to immunize mice. The IC50 value of mouse monoclonal anti-prometryn antibody (mAb) 7D4 (the quantity of analyte that generated 50% prometryn inhibition) was 3.9 ng/mL. The anti-prometryn mAb was of the IgG1 subclass. The IC20 (80% binding level (B/B0) of prometryn)-IC80 (20% binding level (B/B0) of prometryn) range of the anti-prometryn monoclonal antibody standard curve working range was 0.9-18.1 ng/mL. The prepared mAb has good characteristics because it can specifically recognize prometryn, and the cross-reaction rates for ametryn, desmetryn, and terbumeton were 34.77%, 18.09%, and 7.64%, respectively. The cross-reaction rate with the other seven triazines was less than 1%. The hapten structure proposed can serve as an additional tool for modulating selectivity in detecting triazines.

A highly sensitive bio-barcode immunoassay for multi-residue detection of organophosphate pesticides based on fluorescence anti-quenching / 药物分析学报

Balancing the risks and benefits of organophosphate pesticides(OPs)on human and environmental health relies partly on their accurate measurement.A highly sensitive fluorescence anti-quenching multi-residue bio-barcode immunoassay was developed to detect OPs(triazophos,parathion,and chlorpyrifos)in apples,turnips,cabbages,and rice.Gold nanoparticles were functionalized with monoclonal antibodies against the tested OPs.DNA oligonucleotides were complementarily hybridized with an RNA fluorescent label for signal amplification.The detection signals were generated by DNA-RNA hybridization and ribonuclease H dissociation of the fluorophore.The resulting fluorescence signal en-ables multiplexed quantification of triazophos,parathion,and chlorpyrifos residues over the concen-tration range of 0.01-25,0.01-50,and 0.1-50 ng/mL with limits of detection of 0.014,0.011,and 0.126 ng/mL,respectively.The mean recovery ranged between 80.3％and 110.8％with relative standard deviations of 7.3％-17.6％,which correlate well with results obtained by liquid chromatography-tandem mass spectrometry(LC-MS/MS).The proposed bio-barcode immunoassay is stable,reproducible and reliable,and is able to detect low residual levels of multi-residue OPs in agricultural products.

Role of Pigment-Protein Coupling in the Energy Transport Dynamics in the Fenna-Matthews-Olson Complex.

The role of pigment-protein coupling in the dynamics of photosynthetic energy transport in chromophoric complexes has not been fully understood. The excitation energy transfer in the photosynthetic system is tremendously efficient. In particular, we investigate the excitation energy transport in the Fenna-Matthews-Olson (FMO) complex. The exciton dynamics and excitation energy transfer (EET) depend on the interaction between the excited chromophores and their environment. Most theoretical models believe that all bacteriochlorophyll-a (BChla) sites are surrounded by the same local protein environment, which is contradicted by the structural analysis of the FMO complex. Based on different values of pigment-protein coupling for different sites, measured in the adiabatic limit, we have theoretically investigated the effect of the heterogeneous local protein environment on the EET process. By the realistic and site-dependent model of the system-bath couplings, the results show that this interaction may have a critical value for the coherent energy-transfer process. Furthermore, we verify that the two transport pathways are coherent and stable to the important parameter reorganization energy of environmental interactions. The quantum dynamical simulations show that the correlation fluctuation keeps the oscillation of the coherent excitation on a long timescale. In addition, due to the inhomogeneous pigment-protein coupling, different BChl sites have asymmetric excitation oscillation timescales.